Application of the markov model in information technology of the formation of the local socio-economic system

Abstract

The methodology for using Markov models in information technology to support decision-making in the regional and local development management system under conditions of uncertainty is obtained. The organization of cooperation at the local and regional levels is today one of the urgent issues of ensuring national sustainability. After all, in conditions of territorial proximity with the joint use of available resources and infrastructure, forming a single economic environment, the unification of territorial communities (and/or individual cities or villages) into local socio-economic systems allows ensuring effective local development, capacity and sustainability of communities through cooperation, joint use of resources and the resulting synergistic effect from such interaction. Complex dynamic systems are formed, for which it is necessary to ensure the consistency of the interaction of their elements, taking into account competition, increasing load on infrastructure, development of information technologies, changes in the planning of settlements, location of production, etc.
To solve the above problems, the work proposes to use Markov models, models of mass service systems. Based on the fact that most territorial communities have a formed sectoral structure, social sphere facilities, transport highways, etc., the work considers the problem of optimal management of the existing mass transit system. The advantages of using mass transit system models are that their use allows you to take into account the specifics of inter-sectoral interaction at the local and regional levels, to assess the quality of management, having previously found out whether certain influences are available for the system under study. The developed models, methods, algorithms are intended for use in information technology to support decision-making in the system of state and public administration. Its implementation will increase the quality and efficiency of management decisions by optimizing analytical processes.